How do you solve Find the Winner of an Array Game on LeetCode?

Find the Winner of an Array Game (LeetCode #1535) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(1) space complexity. Key insight: If k is greater than or equal to the length of the array, the maximum element will always win.

What is the brute force solution for Find the Winner of an Array Game?

The brute force approach for Find the Winner of an Array Game is Brute Force, with O(n²) time complexity and O(1) space complexity. In the brute-force approach, we simulate the game by repeatedly comparing the first two elements of the array. The winner stays at the front while the loser moves to the end, and we keep track of the number of consecutive wins until one player reaches k wins. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Find the Winner of an Array Game?

Find the Winner of an Array Game uses the following concepts: Array, Simulation. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Find the Winner of an Array Game?

Always consider edge cases, such as when k is very large. Explain your thought process clearly while coding. Practice simulating the game with smaller arrays to build intuition.

What are common mistakes when solving Find the Winner of an Array Game?

Not handling the case where k is greater than or equal to the length of the array. Overcomplicating the simulation by not recognizing when to stop.

#1535

Find the Winner of an Array Game

Medium

ArraySimulationHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(1)

💡

Intuition

Time O(n)Space O(1)

In the optimal approach, we recognize that if k is greater than or equal to the length of the array, the maximum element will always win. Otherwise, we simulate the game but only keep track of the current winner and their win count, which allows us to avoid unnecessary comparisons.

⚙️

Algorithm

3 steps

1Step 1: If k is greater than or equal to the length of the array, return the maximum element.
2Step 2: Initialize the winner and win count.
3Step 3: Iterate through the array, updating the winner and win count based on comparisons.

solution.py20 lines

1# Full working Python code
2
3def find_winner(arr, k):
4    if k >= len(arr):
5        return max(arr)
6    winner = arr[0]
7    win_count = 0
8    i = 1
9    while win_count < k:
10        if winner > arr[i]:
11            win_count += 1
12            i += 1
13        else:
14            win_count = 1
15            winner = arr[i]
16            i += 1
17    return winner
18
19# Example usage
20print(find_winner([2,1,3,5,4,6,7], 2))  # Output: 5

ℹ

Complexity note: The time complexity is O(n) because we only need to iterate through the array once to find the winner, making it efficient even for larger inputs.

1If k is greater than or equal to the length of the array, the maximum element will always win.
2The game can be efficiently simulated by tracking only the current winner and their win count.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.